Impact of Oral Ice Cubes for Prevention of OM among Cancer Patients Receiving Chemotherapy: A Machine Learning Approach
Main Article Content
Abstract
Oral Mucositis (OM) is a painful adversarial consequence of chemotherapy that affects the lining of the mouth and throat. The study goal is to investigate the efficiency of oral ice cubes on OM amongst cancer patients who receive chemotherapy with Machine Learning (ML) based predictive process. Quasi-investigational research was conducted for evaluating the efficacy of oral ice cubes on avoidance/minimization of OM among cancer patients receiving chemotherapy in V.S hospital in Chennai, India. Samples were selected by convenience sampling technique under quasi- investigational two groups namely pre-test and post-test research design. Among the total 60 samples, the first set of 30 samples in experimental group and next set of 30 samples in control group were selected. Before infusing chemotherapy, ice cubes were applied to the oral mucosa for 5 mins and 20 min post chemotherapy session. Observational checklist was assessed before and 7th day post intravenous chemotherapy to assess the clinical manifestations of OM. Naïve Bayes, support vector machine, and XGBoost are used to generate several predictive models. All the ‘t’ values were statistically substancial, demonstrating that there is a substantial difference among the cancer patients undergoing chemotherapy. It depicts the oral ice cube application on the minimizing clinical manifestation of OM was effective among cancer patients post chemotherapy status. It is also reported that there were considerable variations found in the mean total scores and those who received oral ice cubes had minimal clinical manifestation of OM. It can be concluded that oral ice cube application reduced the level of clinical manifestation of OM induced by chemotherapy. Standing orders can be given to all nurses to apply ice cubes to all patients before 5 minutes who receive chemotherapy so that we can minimize or prevent OM in all cancer patients. The same can be included in health policy.